{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "warning: can't import TA-Lib, will be ignored! You can fetch ta-lib from https://www.lfd.uci.edu/~gohlke/pythonlibs/#ta-lib\n",
      "std::cout are redirected to python::stdout\n",
      "std::cerr are redirected to python::stderr\n",
      "2023-10-14 02:24:48.199 [HKU-I] - Using SQLITE3 BaseInfoDriver (BaseInfoDriver.cpp:58)\n",
      "2023-10-14 02:24:48.200 [HKU-I] - Loading market information... (StockManager.cpp:499)\n",
      "2023-10-14 02:24:48.200 [HKU-I] - Loading stock type information... (StockManager.cpp:512)\n",
      "2023-10-14 02:24:48.200 [HKU-I] - Loading stock information... (StockManager.cpp:426)\n",
      "2023-10-14 02:24:48.252 [HKU-I] - Loading stock weight... (StockManager.cpp:529)\n",
      "2023-10-14 02:24:48.630 [HKU-I] - Loading KData... (StockManager.cpp:134)\n",
      "2023-10-14 02:24:48.638 [HKU-I] - Preloading all day kdata to buffer! (StockManager.cpp:157)\n",
      "2023-10-14 02:24:48.639 [HKU-I] - Preloading all week kdata to buffer! (StockManager.cpp:160)\n",
      "2023-10-14 02:24:48.639 [HKU-I] - Preloading all month kdata to buffer! (StockManager.cpp:163)\n",
      "2023-10-14 02:24:48.659 [HKU-I] - 0.03s Loaded Data. (StockManager.cpp:145)\n",
      "Wall time: 1.16 s\n"
     ]
    }
   ],
   "source": [
    "%matplotlib inline\n",
    "%time from hikyuu.interactive import *"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "k = get_kdata('sh000001', -100)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "ename": "UnicodeDecodeError",
     "evalue": "'utf-8' codec can't decode byte 0x9c in position 133: invalid start byte",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mUnicodeDecodeError\u001b[0m                        Traceback (most recent call last)",
      "\u001b[1;32m~\\AppData\\Local\\Temp\\ipykernel_7616\\6354363.py\u001b[0m in \u001b[0;36m<module>\u001b[1;34m\u001b[0m\n\u001b[0;32m      2\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      3\u001b[0m \u001b[1;32mwith\u001b[0m \u001b[0mopen\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m\"temp\"\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;34m'wb'\u001b[0m\u001b[1;33m)\u001b[0m \u001b[1;32mas\u001b[0m \u001b[0mf\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 4\u001b[1;33m     \u001b[0mpickle\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mdump\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mk\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mf\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[1;31mUnicodeDecodeError\u001b[0m: 'utf-8' codec can't decode byte 0x9c in position 133: invalid start byte"
     ]
    }
   ],
   "source": [
    "import pickle\n",
    "\n",
    "with open(\"temp\", 'wb') as f:\n",
    "    pickle.dump(k, f)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "hku_save(k, \"temp\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "k2 = KData()\n",
    "hku_load(k2, \"temp\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1000x800 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "k2.plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.16"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}
